Statistics for Decision Making: Case Study — Mutual Funds to write analysis report Essay Example

Statistics for Decision Making

Case Study: Mutual Funds

Table of Contents

This report presents a case study where the investment analyst conducts an analysis to guide clients regarding investment decision on available mutual funds. SPSS (Statistical Package for Social Scientists) software was used for data entry and statistical analysis. The analyzed variables included: category of shares (small cap, mid cap, large cap); objective – objective of shares comprising the mutual fund–growth or value; assets, fees; expenses ratio; return; risk; best quarter and worst quarter. The performance variables (Expense ratio, 3 year return, 5 year Return and return 2013) were analyzed basing on funds characteristics (Category, Objectives, Risk and Fees). According to the statistical results’ analysis, small cap shares are the best option to consider in share investment plans of the company and individuals, followed by the large cap shares, basing on different characteristics; this information will be availed to the client for them to select among large cap, mid cap and small cap stocks. However, during recession the easier option to venture into is mid cap. In conclusion, the report recommends that the most reasonable investment choice for clients is small cap shares as per the statistical analysis.

Statistics for Decision-Making: Analysis report of case study-mutual funds

1.0 Introduction

Mutual fund is defined as the type of trust by a sponsor where trustees raise money using the sale of units to the public, using various schemes, in order to invest in securities according to the regulations (Gadhi & Perumal, 2016. This report presents a case study where the investment analyst for clients is required to make an analysis for clients. After the analysis, the investment analyst is required to provide guidelines for the clients to make reasonable decisions among the available mutual funds for their retirement account.

1.1 Objectives

• To provide general guidelines for clients to select a fund based on different characteristics

• To guide client to make a reasonable choice among the many funds available

2.0 Business problem

In the current business world, there are numerous investment choices and mutual fund is booming sector that provides an opportunity for investors to generate income and returns (Joshi, 2013). The business problem in the case study involves making a decision to buy mutual funds for investors’ retirement account. Accordingly, the investment analyst is required to make analysis and reach the most suitable decision for clients purchasing mutual funds for their retirement account.

3.0 Methodology

SPSS (Statistical Package for Social Scientists) software was used for data entry and statistical analysis. Descriptive statistics were used to provide an overview of the data. Pearson’s correlation test was used to measure the strength of the association and relationship between the variables. Regression analysis was used to determine overall fit and relative contribution of variables and all predictors.

4.0 Data analysis and interpretation

1. Shares categories Analysis

Data was collected to understand share categories and their respective performance. Analyses are conducted based on frequencies and other descriptive statistics.

Small Caps Performance

Return 2013		5Yr-Return		3-Yr-Return
	48.38333		12.71667		15.69167
Standard Error	1.461605	Standard Error		Standard Error	0.713055
Standard Deviation	11.32154	Standard Deviation	9.227302	Standard Deviation	5.523303
Sample Variance	128.1773	Sample Variance	85.14311	Sample Variance	30.50688
Kurtosis	-0.89565	Kurtosis	-0.58244	Kurtosis	1.002631
Skewness		Skewness	-0.26428	Skewness	-0.39395

From the category analysis of descriptive statistics, small cap category, 2013 returnspresented the highest number of shares (mean of 48.38333) followed closely by 3-year return of 15.69167 shares by mean and finally the 5-year return whose mean was 12.71 shares. This shows that smaller cap mutual funds are preferred on short term than on long term basis.

Figure 1: small cap mean share returns

The data below shows the mid cap category returns.

Return 2013		5Yr-Return		3-Yr-Return
	46.19474		6.210526		15.01579
Standard Error	2.996669	Standard Error	2.059494	Standard Error	1.050404
Standard Deviation	13.06218	Standard Deviation	8.977125	Standard Deviation	4.578605
Sample Variance	170.6205	Sample Variance	80.58877	Sample Variance	20.96363
Kurtosis	0.409484	Kurtosis	-0.72936	Kurtosis	0.194173
Skewness	0.724428	Skewness	0.178491	Skewness	-0.31391

From the descriptive statistics in the mid cap category, 2013 returns presented the highest number of shares (mean of 46.19474 slightly lower than in the small cap) followed by 3-year return, which was almost equal to that of small cap of 15.01579shares by mean and finally the 5-year return whose mean was 6.210526 shares, equal to half of the small cap shares in the same period. This shows that more mid cap mutual funds are equally preferred on short term than on long term basis.

Large cap

Return 2013		5Yr-Return		3-Yr-Return
	32.77381		1.342857		7.097619
Standard Error		Standard Error	0.974537	Standard Error	0.616832
Standard Deviation	9.178609	Standard Deviation	6.315723	Standard Deviation	3.997529
Sample Variance	84.24686	Sample Variance	39.88836	Sample Variance	15.98024
Kurtosis	-0.33242	Kurtosis	-0.63201	Kurtosis
Skewness	0.164818	Skewness	0.395427	Skewness	0.572324

From the statistics table in the large cap category, 2013 returns also presented the highest number of shares with a mean of 32.77381 followed by 3-year return, which was less than half of mid cap of 7.0976 shares by mean and finally the 5-year return whose mean was lowest at 1.342857 shares. The data implies a decrease in returns as the return period increases which means that mutual funds are preferred on short term than on long term basis.

1. Performance of Assets based on growth risk

The table below illustrates data about Performance of mutual fundsbased on various periods of risk.

Table 1: Mean Performance of mutual funds based on risk

Return 2013		5Yr-Return		3-Yr-Return
	41.36207		12.36552		13.15517
Standard Error	1.631596	Standard Error	1.136944	Standard Error	0.765085
Standard Deviation	12.42586	Standard Deviation	8.658705	Standard Deviation	5.826713
Sample Variance		Sample Variance	74.97318	Sample Variance	33.95059
Kurtosis	-0.09275	Kurtosis	-0.99646	Kurtosis	-0.68865
Skewness	0.358427	Skewness	0.129869	Skewness

As shown in the table above, the total sum of assets of mutual funds at low risk category was higher in 2013 returns at 2399 than in 3-year return period whose total was 763 and 5-year return whose sum was smallest at 717.2 or a mean of 12.36.

The table below is a summary of sum and variation of mutual funds at different levels of risk for comparison

Risk level	2013 return	5-Yr-Return	3-Yr-Return
	Sample variation		Sample variation		Sample variation
				74.97318		33.95059
				65.51011		41.87822
High risk		165.2606		104.0426		58.01904

For 2013 returns, the sum of fixed assets of mutual funds dropped as risk increased. Returns were lower during high risk, and highest at low risk. The same trend was replicated for 3-year and 5-year return periods implying risk level influences the rate of return of mutual funds. This is shown in the figure below.

Figure 3: Total assets of shares categories against risk level

It is evident from the bar chart that the shares categories at low risk recorded the highest total sum of asset while the shares categories at high risk recorded the lowest return on investment.

1. Growth and value analysis

The growth patterns for the mutual funds were assessed as per the descriptive statistics shown below.

Return 2013		5-Yr-Return		3-Yr-Return
	40.85306		2.520408		11.09592
Standard Error	1.807517	Standard Error	1.310949	Standard Error	1.017537
Standard Deviation	12.65262	Standard Deviation	9.176646	Standard Deviation	7.122762
Sample Variance	160.0888	Sample Variance	84.21082	Sample Variance	50.73373
Kurtosis	-0.41473	Kurtosis	0.565568	Kurtosis	-0.59167
Skewness	0.321378	Skewness	1.000092	Skewness	0.385748

By mean, the growth pattern was generally low other than in the 2013 return period. The long term 5-year return period specifically performed very poorly recording the lowest mean of 2.520408 shares. By sum, 2013 had the highest sum of shares (2001.8), followed by 3-year return period with about a quarter the value of 2013 period and the lowest sum being for the 5-year return period with 123.5 shares.Value was estimated as shown by the descriptive statistics below.

Return 2013		5Yr-Return		3-Yr-Return
			11.30417		13.62778
Standard Error	1.560812	Standard Error		Standard Error	0.650975
Standard Deviation	13.24393	Standard Deviation	8.447859	Standard Deviation	5.523706
Sample Variance	175.4016	Sample Variance	71.36632	Sample Variance	30.51133
Kurtosis	-0.20505	Kurtosis	-0.84726	Kurtosis	-0.43593
Skewness	0.358646	Skewness	0.111954	Skewness	-0.10369

Using mean as a standard measure of value, 2013 return period had the best value of 43.825 followed by 3-year return period with 13.62 than 5-year return period with 11.30.

1. Quarter and year-interval performance

The survey aimed at determining the best quarter performance as well as year interval performance. Results were as displayed in the table below.

Category
large cap	Sum of Best Quarter
	Sum of 3-Year-Return
	Sum of 5-Year-Return
	Sum of Best Quarter
	Sum of 3-Year-Return
	Sum of 5-Year-Return
small cap	Sum of Best Quarter
	Sum of 3-Year-Return
	Sum of 5-Year-Return
Total Sum of Best Quarter
Total Sum of 3-Year-Return
Total Sum of 5-Year-Return

The small cap shares category recorded the highest sum of best quarter return whose value was 1915.5 followed closely by large cap shares category (1001.9). Mid cap shares category recorded the least return during its best quarter (580.6) compared to the large cap shares category and the small cap shares category. All the three categories recorded lowest returns after 5 years with small cap shares category recording 763, mid cap shares category 118 while large cap recording slightly lower than mid cap (56.4).

Moreover, the small cap shares category recorded more returns in their 3^rd year (941.5) than the one they recorded during the 5^th year (763). The same results were displayed by the large cap shares category that recorded 298.1 in their 3^rd year and 56.4 in their 5^th year. Similarly, mid cap share category displayed the same trend of results recording 285.3 in their 3^rd year and 118 in their 5^th year.

The results in this section imply that returns on shares invested reduced as time increased whose implication was a reduction the capital investments.

1. Expense ratio for shares

The sum of expense ratio for shares categories at low risk was higher (79.92) followed by the sum of expense ratios for average risk shares categories (58.9) while those at high risk recorded the least sum of expense ratio (24.3). This indicates that mutual fund types associated with high risks incur expenditure less than mutual funds with low risks.

Analysis of Expense ratio at various types of mutual funds

Table 5: Expense ratio at various types of mutual funds

Category	Total Expense ratio
Large Cap
Small Cap
Grand Total

The total of expense ratio also varies with the type of mutual funds type.

Figure 2: Expense ratio at various types of mutual funds

As indicated in the figure above, the small cap mutual funds category recorded the highest sum of expense ratio (85.53).The large cap mutual funds category followed closely with 51.73. The mid cap mutual funds category recorded the lowest sum of expense ratio which was 25.69. This shows that the small cap share category spends more than the other types of mutual funds.

1. Assets recorded by the shares categories

The table below shows the sum of assets recorded by the shares categories against the risk level.

Table 3: Sum of Assets

	111952.5
	142743.9
Grand Total	286290.8

The shares category with low risk had the highest sum of assets (142743.9) followed by the shares category with average risk (111952.5) and shares category with high risk recorded the least sum of assets (31594.4). This indicates that the mutual fund types with low risks performed better than those with high risks.

Figure 4: A Pie Chart Showing Shares Categories and Their 2013 Return

Small cap shares category recorded the highest percentage of returns in 2013 followed by large cap shares category. Mid cap shares category recorded the least returns in the year 2013. Small cap shares are therefore the best option to consider in share investment plans of the company and individuals.

1. Mutual funds and fees payment

97 of the mutual funds categories do not pay fees while the remaining 24 pay fees as shown below.

Figure 5: Line graph of mutual funds types against fees payment

1. 4.9 Performance during the worst quarter

Another aspect of the study was finding out the performance of the mutual funds types during their worst quarter.

Table 4: The performance of the mutual funds types during their worst quarter

Category
large cap
small cap
Grand Total

The performance of the small cap mutual funds type was the worst recording a deficit of 1131.5. The performance of the large cap mutual funds type followed with a deficit of 736.8 while the mid cap mutual funds type recorded an average deficit of 366.6 during their worst quarter. This shows that during recession the easier option to venture into is mid cap for such periods.

1. Inferential Statistics

   1. T-Tests for 2013 Returns

Statistical tests were carried out to test 2013 returns. The H₁is that mutual funds will be more viable when invested on short term basis. The null hypothesis (H₀) is that mutual funds will be not be more viable when invested on short term basis.

Separate-Variances T Test for the Difference Between Two Means

(Assumes unequal population variances)

Hypothesized Difference	0
Level of Significance
Population 1 Sample
Sample Size
Sample Mean	42.60515464
Sample Standard Deviation
Population 2 Sample
Sample Size
Sample Mean
Sample Standard Deviation
Intermediate Calculations
Numerator of Degrees of Freedom
Denominator of Degrees of Freedom
Total Degrees of Freedom
Degrees of Freedom
Standard Error
Difference in Sample Means	-0.082345361
Separate-Variance t Test Statistic
Lower-Tail Test
Lower Critical Value
Do not reject the null hypothesis

At 0.05 significant level, the decision rule is: Reject H₀ if Tstat<-1.6820 or Tstat> 0.4876.Do not reject H₀ if -1.6820 ≤Tstat≤ 0.4876. The t statistic is -0.0313 which is within the range of -1.6820 ≤Tstat≤ 0.4876 hence the null hypothesis is not rejected implying that there is no enough evidence to show that short term investment of mutual funds is most viable.

Separate-Variances t Test for the Difference Between Two Means
(assumes unequal population variances)
Hypothesized Difference	0
Level of Significance
Population 1 Sample
Sample Size
Sample Mean	12.41340206
Sample Standard Deviation
Population 2 Sample
Sample Size
Sample Mean	13.36666667
Sample Standard Deviation
Intermediate Calculations		Calculations Area
Numerator of Degrees of Freedom			Pop. 1 Sample Variance
Denominator of Degrees of Freedom			Pop. 2 Sample Variance
Total Degrees of Freedom			Pop. 1 Sample Var./Sample Size
Degrees of Freedom			Pop. 2 Sample Var./Sample Size
Standard Error			For one-tailed tests:
Difference in Sample Means	-0.953264605		TDIST value
Separate-Variance t Test Statistic			1-TDIST value
Lower-Tail Test
Lower Critical Value
Do not reject the null hypothesis

The t-statistic is -0.7260 which falls above the lower critical value and the below the p-value. The implication is that the null hypothesis is not rejected.

Intermediate Calculations
Numerator of Degrees of Freedom
Denominator of Degrees of Freedom
Total Degrees of Freedom
Degrees of Freedom
Standard Error
Difference in Sample Means	-0.75725945
Separate-Variance t Test Statistic
Lower-Tail Test
Lower Critical Value
Do not reject the null hypothesis

There was no sufficient evidence from the t statistic (-0.3182) to prove that 5-year returns are best for mutual fund investment.

Significance of average returns at different risk levels and time

This was estimated through ANOVA test. The 2013 return data in this case is shown in the table below

Anova: Single Factor
				Variance
			48.38333	128.1773
			46.19474	170.6205
			32.77381	84.24686
Source of Variation
Between Groups			3153.775	26.41624	3.31E-10
Within Groups	14087.75		119.3877

In this data, it is hypothesized that Ho: µ1= µ2= µ3 and Ha claiming that at least one of the mean is different from the others at various risk levels. In this case µ1: average mutual fund shares at low risk,µ2: average risk and µ3: high risk. From the data, Fcrit=F0.05, 2, 118= 3.07309. in other words, Ho is rejected when Fcalc>3.07309 and not rejected when Fcalc ≤ 3.07309. From the ANOVA data, Fcalc =26.41624>3.07309.

At the 95% confidence interval, Ho is rejected because Fcalc =26.41624>3.07309. Therefore, there is significant difference of the average returns on mutual funds at low, average and high risk at the 2013 return period.

The values for 5-yr returns

Anova: Single Factor
Source of Variation
Between Groups	3249.257		1624.629	23.63981	2.32E-09
Within Groups	8109.464		68.72427
	11358.72

From the data, Fcalc (23.6398)>F crit (3.07309) meaning that the null hypothesis is rejected providing evidence that supports a significant difference in the average of mutual funds returns at various levels of risk in the 5-year return period. Similar results are obtained for 3-year return period where F (40.74342) >F crit (3.07309) an indicator that the null hypothesis is rejected an implication that there is a significant difference between the mean returns at low, average and high risk for the 5-year period

6.0 General Conclusion

The best types of shares to invest in are the mutual funds in the small cap category. This is because the analysis indicates that the small cap category had the highest number of shares. The next recommended type of share is the large cap shares because this category closely followed the small cap category. The least recommendable type of share is the mid cap category because the analysis indicates that this type had the least shares. In regard to the performance of assets based on their growth, the small cam mutual fund type is the best objective in driving the business. In addition, in regard to the best quarter performance and year-interval performance, the small cap shares category recorded the highest sum of best quarter return whose value was 1915.5 followed closely by large cap shares category (1001.9). Mid cap shares category recorded the least return during its best quarter (580.6) compared to the large cap shares category and the small cap shares category. From the analysis, small cap shares are therefore the best option to consider in share investment plans of the company and individuals.

7.0 Implications

The statistical analysis provides a comparative analysis of proportion of investments of funds invested in various kinds of stocks, namely large cap, mid cap and small cap stocks. In addition, statistical analysis of the portfolio is important in understanding the variability of returns from the mutual funds when compared to previous year. Provided that the statistical analysis the report recommends that the most reasonable investment choice for clients is small cap shares as per the statistical analysis.

7.0 Bibliography

Gadhi K & Perumal R, 2016, Performance of Selected Bank Mutual Fund Schemes Impact in Investors’ Decision Making, International Journal of Advanced Research in Management and Social Sciences, 5(3), pp:361-370.

Jagongo A & Mutswenje V, 2014, A Survey of the Factors Influencing Investment Decisions: The Case of Individual Investors at the NSE, International Journal of Humanities and Social Science, 4(4), pp: 92-102.

Joshi J, 2013, Mutual Funds: An investment option from investors’ point of view, IBMRD’sJournal of Management and Research, 2(1), pp: 124-134.

Krishnan R & Booker D, 2002, Investors’ use of Analysts’ recommendations, Behavioral Research in Accounting, 14(1).

Mohit G & Navdeep A, 2009, Mutual Fund Portfolio Creation Using Industry Concentration, Tura: ICFAI University.